Federated learning (FL) is a novel distributed machine learning paradigm that enables
participants to collaboratively train a centralized model with privacy preservation by …

This article provides a survey of academic literature about field programmable gate array
(FPGA) and their utilization for energy efficiency acceleration in data centers. The goal is to …

With the development of loT and edge computing, data analytics on edge has become
popular, and text analytics directly on compression (TADOC) has been proven to be a …

As sensors operating at the edge continue to evolve, the amount of data that edge devices
need to process is increasing. Cloud computing methods have been proposed to process …

In recent years, hyperspectral imaging technology has been widely applied in agriculture;
however, its complex and redundant data poses significant challenges for implementation …

This article targets the implementation of a bilateral control algorithm for haptic devices on
FPGA platforms, using fixed-point arithmetic (FxP-F) to overcome latency and processing …

Apache Spark has been the most popular in-memory processing framework for big data
applications deployed in data centers. As a CPU-only parallel programming framework …

FPGA accelerator devices have emerged as a powerful platform for implementing high-
performance and scalable solutions in a wide range of industries, leveraging their …

The 2.5 D FPGA integrates 3 or 4 FPGA dies together for larger design capacity and higher
computing power. In this paper, we propose an advanced large neural network accelerator …